From Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth
Statistical Mechanics
2007-05-23 v2 Distributed, Parallel, and Cluster Computing
Computational Physics
Abstract
We study the asymptotic scaling properties of a massively parallel algorithm for discrete-event simulations where the discrete events are Poisson arrivals. The evolution of the simulated time horizon is analogous to a non-equilibrium surface. Monte Carlo simulations and a coarse-grained approximation indicate that the macroscopic landscape in the steady state is governed by the Edwards-Wilkinson Hamiltonian. Since the efficiency of the algorithm corresponds to the density of local minima in the associated surface, our results imply that the algorithm is asymptotically scalable.
Cite
@article{arxiv.cond-mat/9909114,
title = {From Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth},
author = {G. Korniss and Z. Toroczkai and M. A. Novotny and P. A. Rikvold},
journal= {arXiv preprint arXiv:cond-mat/9909114},
year = {2007}
}
Comments
RevTex, 4 pages, 3 figures